Results 11 to 20 of about 5,203 (262)
Journal of Risk and Financial Management, 2020 Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties,
Bernardi Mauro +2 more
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Interpretation of Probabilistic Statements in Science [PDF]
حکمت و فلسفه, 2010 Science often seems to issue statements about probability of some occurrence. In this paper, we will take a look at three different interpretations of probability.
amir ehsan karbasi zadeh +1 more
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Statistical foundations of ecological rationality
Economics: Journal Articles, 2020 If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ...
Brighton Henry
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Bayesianism and inference to the best explanation
Theoria, 2008 Bayesianism and Inference to the best explanation (IBE) are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE.
Valeriano IRANZO
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Bayes and health care research. [PDF]
, 2005 Bayes’ rule shows how one might rationally change one’s beliefs in the light of evidence. It is the foundation of a statistical method called Bayesianism.
A. Chalmers +34 more
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SSRN Electronic Journal, 2011 Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, edited by Nigar Hashimzade and Michael Thornton, forth- coming in 2012 (Edward Elgar Publishing). This chapter presents an introductory review of Bayesian methods for research in empirical macroeconomics.
Bauwens, L, Korobilis, D
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Tort Liability and Unawareness [PDF]
, 2019 Unawareness is a form of bounded rationality where a person fails to conceive all feasible acts or consequences or to perceive as feasible all conceivable act-consequence links.
Chakravarty, Surajeet +2 more
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How Bayesian should Bayesian optimisation be? [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021 Bayesian optimisation (BO) uses probabilistic surrogate models - usually Gaussian processes (GPs) - for the optimisation of expensive black-box functions. At each BO iteration, the GP hyperparameters are fit to previously-evaluated data by maximising the marginal likelihood.
De Ath, George +2 more
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The Principal Principle Implies the Principle of Indifference [PDF]
, 2015 We argue that David Lewis’s principal principle implies a version of the principle of indifference. The same is true for similar principles that need to appeal to the concept of admissibility. Such principles are thus in accord with objective Bayesianism,
Hawthorne, James +3 more
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